Real-time Bidding for Online Advertising: Measurement and Analysis

The real-time bidding (RTB), aka programmatic buying, has recently become the fastest growing area in online advertising. Instead of bulking buying and inventory-centric buying, RTB mimics stock exchanges and utilises computer algorithms to automatically buy and sell ads in real-time; It uses per impression context and targets the ads to specific people based on data about them, and hence dramatically increases the effectiveness of display advertising. In this paper, we provide an empirical analysis and measurement of a production ad exchange. Using the data sampled from both demand and supply side, we aim to provide first-hand insights into the emerging new impression selling infrastructure and its bidding behaviours, and help identifying research and design issues in such systems. From our study, we observed that periodic patterns occur in various statistics including impressions, clicks, bids, and conversion rates (both post-view and post-click), which suggest time-dependent models would be appropriate for capturing the repeated patterns in RTB. We also found that despite the claimed second price auction, the first price payment in fact is accounted for 55.4% of total cost due to the arrangement of the soft floor price. As such, we argue that the setting of soft floor price in the current RTB systems puts advertisers in a less favourable position. Furthermore, our analysis on the conversation rates shows that the current bidding strategy is far less optimal, indicating the significant needs for optimisation algorithms incorporating the facts such as the temporal behaviours, the frequency and recency of the ad displays, which have not been well considered in the past.Comment: Accepted by ADKDD '13 worksho

In the Service of Good Journalism and Audience Interests? How Audience Metrics Affect News Quality

A large and growing body of literature shows that audience metrics exert a significant influence in many newsrooms around the world. Scholars assume that this might affect the quality of news, but findings on how audience metrics influence news quality and media performance are scattered. Based on a widely used set of news quality criteria, this article is the first to focus on this question. It reviews and discusses the existing findings by considering the influence of audience metrics across four analytical dimensions: A) the allocation of resources and recognition; B) the volume, practices and rhythms of news production; C) the selection and placement of topics; and D) the formats and styles of news presentation. The analysis reveals that journalists’ use of audience metrics has a mainly negative impact on news quality. This effect is the result of both the growing economic pressures on newsrooms and a dominant rhetoric that equates measures of audience size with audience interests and good journalistic work

The internet milieu: individualization within a globalised community

Communication technologies have become deeply embedded in our lives, mediating the ways in which information is presented. Due to the global nature of this channel of communication, the world has shrunk and members of the internet may share similar cultural norms of thinking and behaving. Yet, paradoxically, the Internet is personal in that each individual has an interactive opportunity in choosing the options that can expand the breadth and depth of the information they are reading, who they interact with, and the means to achieve that interaction. These options can be expressed through a variety of media techniques. This paper is based on a study of selected websites hosted in English. It looks at language use in the Internet and illustrates the paradoxes between global and individual mediations of meanin

Facebook Recruitment Using Zip Codes to Improve Diversity in Health Research: Longitudinal Observational Study (Preprint)

BACKGROUND Facebook’s advertising platform reaches most US households and has been used for health-related research recruitment. The platform allows for advertising segmentation by age, gender, and location; however, it does not explicitly allow for targeting by race or ethnicity to facilitate a diverse participant pool. OBJECTIVE This study looked at the efficacy of zip code targeting in Facebook advertising to reach blacks/African Americans and Hispanics/Latinos who smoke daily for a quit-smoking web-based social media study. METHODS We ran a general market campaign for 61 weeks using all continental US zip codes as a baseline. Concurrently, we ran 2 campaigns to reach black/African American and Hispanic-/Latino-identified adults, targeting zip codes ranked first by the percentage of households of the racial or ethnic group of interest and then by cigarette expenditure per household. We also ran a Spanish language campaign for 13 weeks, targeting all continental US zip codes but utilizing Facebook’s Spanish language targeting. The advertising images and language were common across campaigns. Costs were compared for advertisement clicks, queries, applications, and participants, and yields were compared for the final three outcomes. We examined outcomes before and after the Cambridge Analytica scandal that broke in March 2018. Finally, we examined 2 promoted Facebook features: lookalike audiences and audience network placement. RESULTS Zip code targeting campaigns were effective for yielding the racial or ethnic groups of interest. The black-/African American–focused versus general market campaign increased black/African American weekly queries (mean 9.48, SD 5.69 vs general market mean 2.83, SD 2.05; P<.001) and applicants (mean 1.11, SD 1.21 vs general market mean 0.54, SD 0.58; P<.001). The Hispanic-/Latino-focused versus general market campaign increased Hispanic/Latino weekly queries (mean 3.10, SD 2.16 vs general market mean 0.71, SD 0.48; P<.001) and applicants (mean 0.36, SD 0.55 vs general market mean 0.10, SD 0.14; P=.001). Cost metrics did not differ between campaigns at generating participants (overall P=.54). Costs increased post- versus prescandal for the black-/African American–focused campaign for queries (mean US $8.51, SD 3.08 vs US$5.87, SD 1.89; P=.001) and applicants (mean US $59.64, SD 35.63 vs US$38.96, SD 28.31; P=.004) and for the Hispanic-/Latino-focused campaign for queries (mean US $9.24, SD 4.74 vs US$7.04, SD 3.39; P=.005) and applicants (mean US $61.19, SD 40.08 vs US$38.19, SD 21.20; P=.001). CONCLUSIONS Zip code targeting in Facebook advertising is an effective way to recruit diverse populations for health-based interventions. Audience network placement should be avoided. The Facebook lookalike audience may not be necessary for recruitment, with drawbacks including an unknown algorithm and unclear use of Facebook user data, and so public concerns around data privacy should be considered. CLINICALTRIAL ClinicalTrial.gov NCT02823028; https://clinicaltrials.gov/ct2/show/NCT0282302

Data-driven marketing for the e-commerce of brands

Project Work presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Business AnalyticsThe topic of this project is a data-driven marketing strategy for an e-commerce shoe brand Lovidovi Shoes. The company wanted to improve their digital marketing performance, and an improvement was defined as an increase in sales. While general best practices for successful Facebook Business advertising have been researched, each business is unique and optimal results are achieved through internal research. Data collected over the course of seven years was first centralized, and then analysed, using tools such as Power BI and Python, in order to determine the best audience and ad settings. The findings made on base data were re-evaluated and fine-tuned through testing. The final result showed that the best performing ads target an audience of women of all ages. Bosnia and Herzegovina makes the brands most profitable market, with the biggest number of sales, and the lowest cost per purchase. The feed placement on Facebook and Instagram get the best reaction, and the bestsellers are products in the white sneakers category. The ads created as part of this project showed significantly better performance by the company’s standards, and average performance by the industry’s standards. This project designed a simple guide on how to start making a shift towards data-driven marketing approaches with a limited budget, and has given the company motivation to utilize its data more and better